Advertisement

GPU-Accelerated Human Motion Tracking Using Particle Filter Combined with PSO

  • Boguslaw Rymut
  • Bogdan Kwolek
  • Tomasz Krzeszowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)

Abstract

This paper discusses how to combine particle filter (PF) with particle swarm optimization (PSO) to achieve better object tracking. Owing to multi-swarm based mode seeking the algorithm is capable of maintaining multimodal probability distributions and the tracking accuracy is far better than accuracy of PF or PSO. We propose parallel resampling scheme for particle filtering running on GPU. We show the efficiency of the parallel PF-PSO algorithm on 3D model based human motion tracking. The 3D model is rasterized in parallel and single thread processes one column of the image. Such level of parallelism allows us to efficiently utilize the GPU resources and to perform tracking of the full human body at rates of 15 frames per second. The GPU achieves an average speedup of 7.5 over the CPU. For marker-less motion capture system consisting of four calibrated cameras, the computations were conducted on four CPU cores and four GTX GPUs on two cards.

Keywords

Particle Swarm Optimization Shared Memory Particle Filter Particle Swarm Optimization Algorithm Global Memory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arulampalam, M., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. Trans. Sig. Proc. 50(2), 174–188 (2002)CrossRefGoogle Scholar
  2. 2.
    Blelloch, G.E.: Prefix sums and their applications. Tech. Rep. CMU-CS-90-190, School of Computer Science, Carnegie Mellon University (November 1990)Google Scholar
  3. 3.
    Box, G.E.P., Muller, M.E.: A note on the generation of random normal deviates. The Annals of Mathematical Statistics 29(2), 610–611 (1958)CrossRefzbMATHGoogle Scholar
  4. 4.
    Deutscher, J., Blake, A., Reid, I.: Articulated body motion capture by annealed particle filtering. In: IEEE Int. Conf. on Pattern Recognition, pp. 126–133 (2000)Google Scholar
  5. 5.
    Doucet, A., Godsill, S., Andrieu, C.: On sequential Monte Carlo sampling methods for bayesian filtering. Statistics and Computing 10(1), 197–208 (2000)CrossRefGoogle Scholar
  6. 6.
    Gong, P., Basciftci, Y.O., Ozguner, F.: A parallel resampling algorithm for particle filtering on shared-memory architectures. In: IEEE Int. Parallel and Distributed Processing Symposium, pp. 1477–1483. IEEE Computer Society (2012)Google Scholar
  7. 7.
    Harris, M., Sengupta, S., Owens, J.D.: Parallel prefix sum (scan) with CUDA. In: Nguyen, H. (ed.) GPU Gems 3. Addison Wesley (August 2007)Google Scholar
  8. 8.
    Hoberock, J., Bell, N.: Thrust: A parallel template library, version 1.3.0 (2010), http://www.meganewtons.com/
  9. 9.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. of IEEE Int. Conf. on Neural Networks, pp. 1942–1948. IEEE Press, Piscataway (1995)CrossRefGoogle Scholar
  10. 10.
    Krzeszowski, T., Kwolek, B., Wojciechowski, K.: Articulated body motion tracking by combined particle swarm optimization and particle filtering. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2010, Part I. LNCS, vol. 6374, pp. 147–154. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Kwolek, B., Krzeszowski, T., Gagalowicz, A., Wojciechowski, K., Josinski, H.: Real-time multi-view human motion tracking using particle swarm optimization with resampling. In: Perales, F.J., Fisher, R.B., Moeslund, T.B. (eds.) AMDO 2012. LNCS, vol. 7378, pp. 92–101. Springer, Heidelberg (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Boguslaw Rymut
    • 2
  • Bogdan Kwolek
    • 1
  • Tomasz Krzeszowski
    • 2
  1. 1.AGH University of Science and TechnologyKrakówPoland
  2. 2.Rzeszów University of TechnologyRzeszówPoland

Personalised recommendations